Evaluation of different few-shot learning methods
Seminars
Laboratory of Information Technologies
Joint Laboratory Seminar
Date and Time: Tuesday, 2 July 2024, at 3:00 PM
Venue: room 310, Meshcheryakov Laboratory of Information Technologies, online on Webinar
Seminar topic: “Evaluation of different few-shot learning methods for plant disease classification”
Speaker: Alexander Uzhinsky
Convolutional neural networks (CNNs) have been successfully used for image classification for over a decade. Previously, achieving good results required tens of thousands of images per class. Now, using few-shot and one-shot learning approaches, it is possible to obtain a model with decent performance even when only a few images per class are available. The seminar will cover general concepts of neural networks, convolutional neural networks, methods for data preparation and model training, approaches to training under few-shot learning conditions, and the results of studies related to plant disease classification.